• Bulletin of the Korean Chemical Society
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• v.32 no.7
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• pp.2332-2338
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• 2011

In this study, we proposed a new promising idea of utilizing moving window principal component analysis (MWPCA) as a sensitive diagnostic tool to detect the presence of peak position shift. In this approach, the moving window is constructed from a small data segment along the wavenumber axis. For each window bound by a narrow wavenumber region, separate PCA analysis was applied. Simulated spectra with complex spectral feature variations were analyzed to explore the possibility of MWPCA technique. This MWPCA-based detection of the peak shift, potentially coupled with 2D correlation analysis to provide additional verification, may offer an attractive solution.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.397-400
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• 2007

For mapping the distribution of heavy metals in the mining area, field spectroscopy and hyperspectral remote sensing were used in this study. Although heavy metals are spectrally featureless from the visible to the short wave infrared range, possible variations in spectral signal due to heavy metals bound onto minerals can be explained with the metal binding reaction onto the mineral surface. Variations in the spectral absorption shapes of lattice OH and oxygen on the mineral surface due to the combination of heavy metals were surveyed over the range from 420 to 2400 nm. Spectral parameters such as peak ratio and peak area were derived and statistically linked to metal concentration levels in the streambed samples collected from the dry stream channels. The spatial relationships between spectral parameters and concentrations of heavy metals were yielded as well. Based on the observation at a ground level for the relationship between spectral signal and metal concentration levels, the spectral parameters were classified in a hyperspectral image and the spatial distribution patterns of classified pixels were compared with the product of analysis at the ground level. The degree of similarity between ground dataset and image dataset was statistically validated. These techniques are expected to support assessment of dispersion of heavy metal contamination and decision on optimal sampling point.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.279-286
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• 2006

Classification method used in this paper is applied for the first time to Korean traditional music. Among the frequency distribution vectors, average peak value is suggested and proved effective comparing to previous classification success rate. Mean, variance, spectral centroid, average peak value and ZCR are used to classify Korean traditional musical instruments. To achieve Korean traditional instruments automatic classification, Spectral analysis is used. For the spectral domain, Various functions are introduced to extract features from the data files. k-NN classification algorithm is applied to experiments. Taegum, gayagum and violin are classified in accuracy of 94.44% which is higher than previous success rate 87%.

• Journal of the Korean Society for Nondestructive Testing
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• v.34 no.6
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• pp.419-427
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• 2014

Nonlinear features of ultrasonic waves are more sensitive to the presence of a fatigue crack than their linear counterparts are. For this reason, the use of nonlinear ultrasonic techniques to detect a fatigue crack at its early stage has been widely investigated. Of the different proposed techniques, laser nonlinear wave modulation spectroscopy (LNWMS) is unique because a pulse laser is used to exert a single broadband input and a noncontact measurement can be performed. Broadband excitation causes a nonlinear source to exhibit modulation at multiple spectral peaks owing to interactions among various input frequency components. A feature called maximum sideband peak count difference (MSPCD), which is extracted from the spectral plot, measures the degree of crack-induced material nonlinearity. First, the ratios of spectral peaks whose amplitudes are above a moving threshold to the total number of peaks are computed for spectral signals obtained from the pristine and the current state of a target structure. Then, the difference of these ratios are computed as a function of the moving threshold. Finally, the MSPCD is defined as the maximum difference between these ratios. The basic premise is that the MSPCD will increase as the nonlinearity of the material increases. This technique has been used successfully for localizing fatigue cracks in metallic plates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.1
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• pp.322-340
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• 2012

Orthogonal Frequency Division Multiplexing (OFDM) is usually regarded as a spectral efficient multicarrier modulation technique, yet it suffers from a high peak-to-average power ratio (PAPR) problem. Among all the existing PAPR reduction techniques in OFDM systems, side information based PAPR reduction techniques such as partial transmit sequence (PTS) and selective mapping (SLM) schemes, have attracted the most attention. However, the transmission of side information results in somewhat spectral loss and this does not significantly improve the bit error rate (BER) performance. Parallel combinatory (PC) OFDM yields higher spectral efficiency (SE) and better BER performance on Gaussian channels,while is a little but not obvious PAPR improvement over the ordinary OFDM system. This investigation aimed to design a 'perfect' OFDM system. We introduce the side information to rotate the subcarrier phases of our novel PC-OFDM system structure, and call this new system the SIPC(Side information based Parallel Combinatory)-OFDM system. The proposed system achieves better PAPR and SE performance. In addition, considering the tradeoff of system parameters, the proposed system also has the properties of a higher BER.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.547-553
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• 2003

In this paper, we designed the PC-based analyzer of the power spectral density that could estimate the heart rate variability from time series data of R-R interval. The power spectral density estimated that it applied the autoregressive model to the measured electrocardiogram during a short period. Also, the characteristics of the designed analyzer are that it could process of the signal filtering, the generation and recomposition of time series and the feature extraction at the same time. Especially the analyzer reconstructed which applied the lowpass filter of the time series composed by the linear interpolation so as to enhance the signal-to-noise feature. We could estimate the power spectral density that confirmed a variety of power peak with low frequency range and high frequency rang of autonomic nerve by the heart rate variability.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.110.2-110.2
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• 2012

We investigate a cool loop and a dark lane over a limb active region on 2007 March 14 by the Hinode/EUV Imaging Spectrometer (EIS). The cool loop is clearly seen in the EIS spectral lines formed at the transition region temperature (log T = 5.8). The dark lane is characterized by an elongated faint structure in coronal spectral lines (log T = 5.8 - 6.1) and rooted on a bright point. We examine their electron densities, Doppler velocities, and non-thermal velocities as a function of distance from the limb using the spectral lines formed at different temperatures (log T = 5.4 - 6.4). The electron densities of the cool loop and the dark lane are derived from the density sensitive line pairs of Mg VII, Fe XII, and Fe XIV spectra. Under the hydrostatic equilibrium and isothermal assumption, we determine their temperatures from the density scale height. Comparing the scale height temperatures to the peak formation temperatures of the spectral lines, we note that the scale height temperature of the cool loop is consistent with a peak formation temperature of the Mg VII (log T = 5.8) and the scale height temperature of the dark lane is close to a peak formation temperature of the Fe XII and Fe XIII (log T = 6.1 - 6.2). It is interesting to note that the structures of the cool loop and the dark lane are most visible in these temperature lines. While the non-thermal velocity in the cool loop slightly decreases (less than 7 km $s^{-1}$) along the loop, that in the dark lane sharply falls off with height. The variation of non-thermal velocity with height in the cool loop and the dark lane is contrast to that in off-limb polar coronal holes which are considered as source of the fast solar wind. Such a decrease in the non-thermal velocity may be explained by wave damping near the solar surface or turbulence due to magnetic reconnection near the bright point.

• Bulletin of the Korean Chemical Society
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• v.24 no.7
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• pp.967-970
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• 2003

A new modified singular value decomposition method, piecewise polynomial truncated SVD (PPTSVD), which was originally developed to identify discontinuity of the earth's radial density function, has been used for large solvent peak suppression and noise elimination in nuclear magnetic resonance (NMR) signal processing. PPTSVD consists of two algorithms of truncated SVD (TSVD) and L₁ problems. In TSVD, some unwanted large solvent peaks and noise are suppressed with a certain soft threshold value, whereas signal and noise in raw data are resolved and eliminated in L₁ problems. These two algorithms were systematically programmed to produce high quality of NMR spectra, including a better solvent peak suppression with good spectral line shapes and better noise suppression with a higher signal to noise ratio value up to 27% spectral enhancement, which is applicable to multidimensional NMR data processing.

• The Journal of the Acoustical Society of Korea
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• v.31 no.3
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• pp.179-187
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• 2012

This paper presents a novel method for estimating reliable noise spectral magnitude for acoustic background noise suppression where only a single microphone recording is available. The proposed method finds noise estimates from spectral magnitudes measured at line spectral frequencies (LSFs), under the observation that adjacent LSFs are near the peak frequencies and isolated LSFs are close to the relatively flattened valleys of LPC spectra. The parameters used in the proposed method are LPC coefficients, their corresponding LSFs, and the gain of LPC residual signals, so it suits well to LPC-based speech coders.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7C
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• pp.672-679
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• 2006

Cognitive radio, which is designed to dynamically adapt its transmission to the environments, is believed to be one of the fundamental techniques for future spectrum utilization. As the first step of cognitive radio, spectrum sensing is treated as the most important technique, through which cognition is well explained. In this paper, we propose a spectral correlation based detection method for spectrum sensing. An unlicensed secondary user system operating in TV broadcast bands is taken as an example. Based on the cyclostationarity of communication signals, spectral correlation function is used to minimize the effect of random noise and interference. Energy measurement and peak detection based criteria are proposed. Simulation results show that the proposed detection method outperforms the energy detection and is more suitable for spectrum sensing in cognitive radios.